Mr. Wei Wang Profile

Wei Wang

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Proceedings Article | 5 June 2024 Paper

Defect detection of voltmeter in distributed electricity room based on improved deformable DETR

Haiming Gong, Mengen Sun, Xiangge Guo, Yi Wu, Wei Wang, Jie Zheng

Proceedings Volume 13163, 1316334 (2024) https://doi.org/10.1117/12.3030256

KEYWORDS: Deformation, Defect detection, Education and training, Object detection, Ablation, Performance modeling, Transformers, Inspection, Data modeling, Calibration

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Voltmeter defect detection is a critical component in the calibration pipeline of electric meters. Traditional calibration methods heavily rely on manual inspection, resulting in time-consuming procedures with high rates of misjudgment. The scarcity of authentic samples containing defects poses challenges in constructing a sufficiently abundant dataset for defect samples. However, current Deformable DETR demonstrates suboptimal performance on small-scale datasets. One factor contributing to its underperformance on small-scale datasets is the excessive redundancy present in queries within the encoder, posing challenges for the model to effectively concentrate on objects. Moreover, the Hungarian matching in Deformable DETR results in a scarcity of positive examples, which hampers convergence speed. This paper introduces enhancements to Deformable DETR, including a sparse encoder and a hybrid matching mechanism, aimed at resolving the slow convergence problem on small-scale datasets. Finally, extensive experiments on our dataset validate the superior effectiveness of our proposed method, achieving the best performance in defect detection.

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